Thomas Barnes

Payments don't pause while 90 people pile onto a bridge to work out who owns a failure. Traditional L1 triage is an expensive bottleneck which consumes valuable engineering capacity where operations and engineers piece together what happened, who is affected, and who needs to respond. Meanwhile, customers are feeling the impact.

We're using AI to change that: turning observability data, operational knowledge, and business context into actionable incident intelligence before the bridge even starts.

• Ending the guessing game: Using AI to map service dependencies, identify affected customers, and establish the likely blast radius in seconds
• Replacing the bridge: Bringing together telemetry, historical incidents, ownership, and operational knowledge to give responders evidence-based hypotheses and get the incident to the right team faster
• Making expertise scalable: Reducing our dependence on tribal knowledge and individual muscle memory by turning years of operational experience into intelligence
• Proving the business value: Reducing MTTI and MTTR, minimising unnecessary incident mobilisation, and giving leaders earlier visibility of customer and revenue impact

This isn't about replacing the people who know how to fix incidents. It's about making sure we only need to call them when they're actually needed.

Standardisation accelerates teams when it removes friction - but over-centralisation creates bottlenecks. The goal is consistent telemetry and governance without preventing teams from shipping.